autonomy build, phase 1
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serversdwn
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cortex/tests/test_autonomy_phase1.py
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197
cortex/tests/test_autonomy_phase1.py
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"""
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Integration tests for Phase 1 autonomy features.
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Tests monologue integration, executive planning, and self-state persistence.
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"""
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import asyncio
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import json
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import sys
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import os
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# Add parent directory to path for imports
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from autonomy.monologue.monologue import InnerMonologue
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from autonomy.self.state import load_self_state, update_self_state, get_self_state_instance
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from autonomy.executive.planner import plan_execution
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async def test_monologue_integration():
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"""Test monologue generates valid output."""
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print("\n" + "="*60)
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print("TEST 1: Monologue Integration")
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print("="*60)
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mono = InnerMonologue()
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context = {
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"user_message": "Explain quantum computing to me like I'm 5",
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"session_id": "test_001",
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"self_state": load_self_state(),
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"context_summary": {"message_count": 5}
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}
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result = await mono.process(context)
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assert "intent" in result, "Missing intent field"
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assert "tone" in result, "Missing tone field"
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assert "depth" in result, "Missing depth field"
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assert "consult_executive" in result, "Missing consult_executive field"
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print("✓ Monologue integration test passed")
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print(f" Result: {json.dumps(result, indent=2)}")
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return result
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async def test_executive_planning():
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"""Test executive planner generates valid plans."""
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print("\n" + "="*60)
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print("TEST 2: Executive Planning")
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print("="*60)
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plan = await plan_execution(
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user_prompt="Help me build a distributed system with microservices architecture",
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intent="technical_implementation",
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context_state={
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"tools_available": ["RAG", "WEB", "CODEBRAIN"],
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"message_count": 3,
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"minutes_since_last_msg": 2.5,
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"active_project": None
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},
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identity_block={}
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)
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assert "summary" in plan, "Missing summary field"
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assert "plan_text" in plan, "Missing plan_text field"
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assert "steps" in plan, "Missing steps field"
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assert len(plan["steps"]) > 0, "No steps generated"
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print("✓ Executive planning test passed")
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print(f" Plan summary: {plan['summary']}")
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print(f" Steps: {len(plan['steps'])}")
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print(f" Complexity: {plan.get('estimated_complexity', 'unknown')}")
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return plan
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def test_self_state_persistence():
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"""Test self-state loads and updates."""
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print("\n" + "="*60)
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print("TEST 3: Self-State Persistence")
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print("="*60)
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state1 = load_self_state()
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assert "mood" in state1, "Missing mood field"
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assert "energy" in state1, "Missing energy field"
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assert "interaction_count" in state1, "Missing interaction_count"
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initial_count = state1.get("interaction_count", 0)
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print(f" Initial interaction count: {initial_count}")
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update_self_state(
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mood_delta=0.1,
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energy_delta=-0.05,
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new_focus="testing"
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)
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state2 = load_self_state()
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assert state2["interaction_count"] == initial_count + 1, "Interaction count not incremented"
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assert state2["focus"] == "testing", "Focus not updated"
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print("✓ Self-state persistence test passed")
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print(f" New interaction count: {state2['interaction_count']}")
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print(f" New focus: {state2['focus']}")
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print(f" New energy: {state2['energy']:.2f}")
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return state2
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async def test_end_to_end_flow():
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"""Test complete flow from monologue through planning."""
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print("\n" + "="*60)
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print("TEST 4: End-to-End Flow")
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print("="*60)
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# Step 1: Monologue detects complex query
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mono = InnerMonologue()
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mono_result = await mono.process({
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"user_message": "Design a scalable ML pipeline with CI/CD integration",
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"session_id": "test_e2e",
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"self_state": load_self_state(),
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"context_summary": {}
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})
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print(f" Monologue intent: {mono_result.get('intent')}")
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print(f" Consult executive: {mono_result.get('consult_executive')}")
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# Step 2: If executive requested, generate plan
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if mono_result.get("consult_executive"):
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plan = await plan_execution(
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user_prompt="Design a scalable ML pipeline with CI/CD integration",
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intent=mono_result.get("intent", "unknown"),
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context_state={"tools_available": ["CODEBRAIN", "WEB"]},
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identity_block={}
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)
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assert plan is not None, "Plan should be generated"
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print(f" Executive plan generated: {len(plan.get('steps', []))} steps")
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# Step 3: Update self-state
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update_self_state(
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energy_delta=-0.1, # Complex task is tiring
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new_focus="ml_pipeline_design",
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confidence_delta=0.05
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)
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state = load_self_state()
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assert state["focus"] == "ml_pipeline_design", "Focus should be updated"
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print("✓ End-to-end flow test passed")
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print(f" Final state: {state['mood']}, energy={state['energy']:.2f}")
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return True
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async def run_all_tests():
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"""Run all Phase 1 tests."""
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print("\n" + "="*60)
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print("PHASE 1 AUTONOMY TESTS")
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print("="*60)
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try:
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# Test 1: Monologue
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mono_result = await test_monologue_integration()
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# Test 2: Executive Planning
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plan_result = await test_executive_planning()
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# Test 3: Self-State
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state_result = test_self_state_persistence()
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# Test 4: End-to-End
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await test_end_to_end_flow()
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print("\n" + "="*60)
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print("ALL TESTS PASSED ✓")
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print("="*60)
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print("\nSummary:")
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print(f" - Monologue: {mono_result.get('intent')} ({mono_result.get('tone')})")
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print(f" - Executive: {plan_result.get('estimated_complexity')} complexity")
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print(f" - Self-state: {state_result.get('interaction_count')} interactions")
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return True
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except Exception as e:
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print("\n" + "="*60)
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print(f"TEST FAILED: {e}")
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print("="*60)
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import traceback
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traceback.print_exc()
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return False
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if __name__ == "__main__":
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success = asyncio.run(run_all_tests())
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sys.exit(0 if success else 1)
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